Land mobile radio systems as used for dispatch applications, and also many wireless cellular systems, use frequency modulation which has proven to be well suited to the application by reason of immunity to impulse noise which is common in the vehicular environment. Such systems are increasingly being required to transmit data as well as analog speech and advances in computer technology have increased the demand for higher bit rates for data transfer.
Radio frequencies are regulated. While demands for higher bit rates are wide spread, regulatory agencies have not increased the bandwidth needed to facilitate high speed data transmission. In fact, the trend is in the opposite direction. In 1997 the Federal Communications Commission mandated the use of channels which are one half or one quarter as wide as those previously authorized. As taught by Shannon and Nyquist, there is a proven relationship between the bit rate of a channel, the bandwidth of the channel and the signal to noise ratio required to decode the data accurately. As the bit rate increases, all else being equal, the signal to noise ratio required to decode the data is also increased, and thus the range of the radio system is reduced as the bit rate increases.
Land mobile and cellular channels differ from those used in fixed microwave point to point services and satellite systems by virtue of reflections and fading of the signals. Signals arriving at or from a wireless communications device such as a mobile radio receiver or cellular telephone are almost always comprised of a complex amalgam of waves, some directly from the sending antenna and others reflected from stationary and moving objects. In the worst case scenario, the total received signal is composed of reflected signals. The resulting waveform caused by the combination of reflected signals (worse case) and/or direct signal plus reflected signals, is subject to cancellation or reinforcement in the amplitude domain as well as distortion in the time domain resulting from propagation delays over the varying length paths taken by reflected signals. Both the amplitude and time distortions make decoding of the signals more difficult. It is not uncommon for cancellation to reduce the incoming signal to a level far below the threshold required for reliable decoding by the receiver. This effect is referred to as multi-path fading.
In data systems, such cancellations or “drop outs” erase portions of the desired bit stream. The duration of the erasure is a function of the average signal strength, the wavelength of the radio signal, the speed of the vehicle (where the wireless device is being operated in a vehicle) and that of moving reflectors in the vicinity. Forward Error Correction (FEC) is a common technique for solving this erasure problem. Redundant information is added to the transmitted data to allow for a predicted level of erasures and recovery of the original data without retransmission. FEC is useful but as the bit rate increases, more and more redundancy must be added which leads to diminishing returns. The redundancy reduces the effective bit rate of the system.
Another solution to problems caused by multi-path fading is to increase the complexity of the receiving system. Fading can be mitigated by using multiple receivers and multiple antennas. Such systems are often called diversity receivers since they are based on spatial diversity. Two or more receivers with separate antennae spaced an appropriate distance apart from each other so that the received signals are non-correlated give rise to probabilities that destructive interference experienced at one antenna may not be present on another.
Spatial diversity receiving systems generally use one of three different classes of techniques to combine the multiple signals, being: (i) selection combining whereby the best signal is chosen based on assessment of signal strength (i.e. the signal having the best signal-to-noise ratio); (ii) equal gain combining whereby all signals are combined together regardless of the strength of any individual signal; and (iii) optimal combining whereby the signals are combined proportionally based on their individual strengths. Only the latter attempts to make use of the maximum possible information content available from all signals to yield optimal performance. However, in practice, it has been difficult to design combiner circuitry which effectively combines signals on such an optimal basis, the problem being to develop effective and practical algorithms for determining the weights to be applied. Many known optimal combiners use complex equalizers to implement an estimation of the received symbol sequences which is then used to proportionally weight the received signals for combining purposes. Such systems are exemplified by the following patent references.
Each of U.S. Pat. No. 5,499,272 (Bottomley) and U.S. Pat. No. 5,701,333 (Okanoue et al) apply complex estimation algorithms to, in effect, produce a synthesized received data stream. U.S. Pat. No. 5,862,192 (Huszar et al) also applies an estimation algorithm but it compares estimated sequences to sample sequences, and selects received sequences on the basis of this comparison. U.S. Pat. No. 5,901,174 (Richard) applies weightings to the received channels which are derived from channel error estimations based on a global estimation algorithm. Another system, described in U.S. Pat. No. 5,640,695 (Fitzgerald), uses a continuously switching logic control mechanism for audio signals (this being a type of selective combiner). U.S. Pat. No. 4,972,434 (Le Polozec et al) uses an adaptive (feedback type) equalizer to derive a distortion factor which is used to weight signal strength measurements for a combiner such that the distortion factor is based on the combined signal produced by the combiner.
Accordingly, there is a need for an effective means of optimally combining signals in a spatial diversity receiver which is less complex than those of the prior art.